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用时空随机森林模型估计在瑞士的每日空气中花粉度的历史估计

Behzad Valipour Shokouhi1, Kees de Hoogh1, Regula Gehrig2

  • 1Swiss Tropical and Public Health Institute, Allschwil, Switzerland; University of Basel, Basel, Switzerland.

The Science of the total environment
|September 24, 2023
PubMed
概括

准确的每日花粉度预测对于了解过敏影响至关重要. 瑞士的一种新的时空机器学习模型显示出高准确度,使用环境数据预测健康研究的花粉水平.

关键词:
土地使用回归.机器学习是机器学习.花粉花粉花粉的花粉公共卫生 公共卫生随机的森林 随机的森林时间空间模型.

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Linear Approximations01:23

Linear Approximations

For a differentiable function of two variables, linear approximation estimates values near a known point by replacing the curved surface with its tangent plane. Consider the function\begin{equation*}f(x,y)=x^2+3y^2\end{equation*}near the point (2, 1). The exact value at this point is f(2, 1) = 22 + 3(1)2 = 4 + 3 = 7.The linear approximation of f(x, y)) near (a, b) is\begin{equation*}L(x,y)=f(a,b)+f_x(a,b)(x-a)+f_y(a,b)(y-b)\end{equation*}First, compute the partial derivatives: fx(x, y) = 2x and...